نوع مقاله : مقاله پژوهشی

نویسندگان

گروه مهندسی ماشین های کشاورزی، دانشکده مهندسی و فناوری کشاورزی، پردیس کشاورزی و منابع طبیعی دانشگاه تهران، کرج، ایران

چکیده

سابقه و هدف:
توسعه پایدار ایجاب می­ کند که تأمین انرژی مورد نیاز بصورت پایدار، با هزینه ­ای قابل قبول و با کمترین اثر­های منفی اجتماعی و محیط زیستی صورت گیرد. بنابراین بهینه‌سازی مصرف انرژی و در نتیجه کاهش انتشار آلاینده­ های محیط زیستی از اهمیت ویژه‌ای برخوردار می‌باشد. هدف از این پژوهش بررسی میزان مصرف انرژی و انتشار آلاینده­ ها و در نهایت بهینه ­سازی مصرف انرژی با استفاده از روش ­های مرسوم بهینه ­سازی از جمله تحلیل پوششی داده­ ها و الگوریتم ژنتیک با هدف کاهش انتشارات محیط زیستی در صنعت تولید کیک در استان گیلان بود.
مواد و روش ­ها:
با استفاده از مدل ­های تحلیل پوششی داده ­ها، واحدهای کارا و ناکارا در مصرف انرژی شناسایی شدند. براساس الگوی مصرف انرژی واحدهای کارا، الگوی مصرف بهینه انرژی برای دیگر واحدها بیان شد و ارزیابی محیط زیستی براساس الگوی بهینه انجام شد. در­نهایت، با استفاده از روش الگوریتم ژنتیک و با در نظر گرفتن دو تابع هدف بمنظور افزایش عملکرد و کاهش شاخص گرمایش­ جهانی، الگوی بهینه مصرف انرژی در دیگر واحدهای تولید کیک بیان شد.   
نتایج و بحث:
نتایج این پژوهش نشان داد که میزان 260532.25 مگاژول انرژی برای تولید روزانه 4157.14 کیلوگرم کیک مصرف شده است. بیشترین سهم انرژی مصرفی به گاز طبیعی با 128582.1مگاژول اختصاص داشت. همچنین سنجه گرمایش جهانی برای تولید هر تن کیک  kg CO2 eq.13099.49 تعیین شد. بر اساس نتایج تحلیل پوششی داده­ ها، از مجموع 21 واحد تولیدی کیک، 17 واحد براساس مدل بازگشت به مقیاس متغیر کارا شناخته شدند. براساس نتایج مدل­ های تحلیل پوششی داده­ها، میزان کل انرژی موردنیاز در حالت مصرف بهینه نهاده ­ها، درصد صرفه‌جویی انرژی و کاهش سنجه گرمایش جهانی بترتیب برابر 254929.28 مگاژول در روز، 2.15 درصد و kg CO2 eq. 550.18 به ازای تولید یک تن کیک تعیین شدند. همچنین الگوی مصرف انرژی بیان شده توسط الگوریتم ژنتیک چند هدفه منجر به کاهش 36.30 درصدی در مصرف انرژی شد که بیشترین درصد صرفه ­جویی در انرژی مربوط به نیروی کارگری بود. بر اساس نتایج بهینه ­سازی چندهدفه، میزان گرمایش جهانی به ازای تولید یک تن کیک برابر kg CO2 eq. 10038.44 تعیین شد.
نتیجه ­گیری:
بهینه‌سازی چند­هدفه با الگوریتم ژنتیک در مقایسه با بهینه­ سازی با تحلیل پوششی داده­ ها، منجر به کاهش بیشتر انرژی مصرفی، گرمایش ­جهانی، هزینه ­های تولید و بارهای محیط زیستی و همچنین افزایش بیشتر درآمد شد. بنابراین استفاده از روش الگوریتم ژنتیک، راه را برای رسیدن به توسعه پایدار در صنعت تولید کیک و باقی­ماندن در عرصه رقابت با دیگر صنایع غذایی هموار خواهد کرد.

کلیدواژه‌ها

عنوان مقاله [English]

Optimization of energy consumption and reduction of environmental emissions in cake production using data envelopment analysis and genetic algorithm

نویسندگان [English]

  • Asadollah Akram
  • Majid Khanali
  • Mahdieh Mohammadnia Galeshklamei
  • Homa Hosseinzadeh-Bandbafha

Department of Agricultural Machinery Engineering, Faculty of Agricultural Engineering and Technology, University of Tehran, Karaj, Iran

چکیده [English]

Introduction:
Sustainable development necessitates the supply of energy resources in a sustainable manner, with a reasonable cost and with minimum negative social and environmental impacts. Thus the optimization of energy consumption, and as a result, the reduction of environmental emissions is of particular importance. The purpose of this study was to assess the amounts of consumed energy and pollutant emissions, optimization of energy consumption, and reduction in environmental emissions in the cake production industry in Guilan Province using data envelopment analysis (DEA) and genetic algorithm (GA).
Material and methods:
The efficient and inefficient units considering energy consumption were identified using DEA models. The optimal energy consumption pattern based on efficient units was presented for other cake production units, and the environmental assessment was performed based on the optimal pattern. Finally, using the multi-objective genetic algorithm (MOGA) and considering two objective functions aiming at increasing the yield and reducing the global warming (GW) index, the optimal energy consumption pattern in cake production units was presented.
Results and discussion:
The results of this study showed that 260532.25 MJ of energy was consumed for a daily production of 4157.14 kg of cake. The highest share of energy consumption was allocated to natural gas with 128582.1 MJ. Also, GW index was calculated 13099.49 kg CO2 eq. per ton of produced cake.According to DEA results, from a total of 21 cake production units, 17 units were recognized efficient based on variable returns to scale model. Based on DEA results, the total energy consumption for optimum consumption of inputs, the energy saving percentage, and the reduction of GW index were determined 254929.28 MJ day-1, 2.15%, and 550.18 kg CO2 eq. per ton of produced cake, respectively. Also, the energy use pattern proposed by the MOGA resulted in 36.3% reduction of energy consumption, in which the highest percentage of energy savings was associated with human labor. Based on the optimization results of MOGA, GW index for production of one ton of cake was calculated 10038.44 kg CO2 eq.
Conclusion:
MOGA optimization method in comparison to DEA, resulted in more reduction of energy consumption, GW index, production costs, and environmental burdens as well as higher income. Thus, the use of MOGA will pave the way for achieving sustainable development in cake production industry and staying in competition with other food industries.

کلیدواژه‌ها [English]

  • Genetic algorithm
  • Energy
  • Data Envelopment Analysis
  • Cake
  • Global warming

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